Photovoltaic cluster operation control system and method

Abstract

The invention discloses a photovoltaic cluster operation control system and method, and relates to the technical field of photovoltaic control, and the method comprises the steps: 1, starting to collect voltage data, illumination intensity data and signal data in real time, and carrying out the comprehensive analysis to obtain an interference factor; 2, judging whether the operation of the photovoltaic cluster is interfered or not according to the interference factor; and step 3, if interference is judged, regulation and control are carried out through an anti-interference module, and if the interference is judged to be normal, detection is ended. Voltage, illumination intensity and signal data are collected in real time and fused into a comprehensive interference factor through time sequence difference and standardization processing, the limitation of single parameter detection is broken through, multi-source interference is systematically quantized, a preset threshold value is compared with the interference factor, an interference source is actively shielded by the anti-interference module, real-time dynamic response is achieved, equipment misoperation is avoided, and the detection accuracy is improved. And the operation stability of the photovoltaic cluster in a complex environment is improved.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic control technology, and in particular to a photovoltaic cluster operation control system and method. Background Art

[0002] With the deepening promotion of the dual carbon goals, photovoltaic energy, as the core carrier for achieving energy structure transformation, has become an inevitable trend in large-scale and clustered development. By integrating distributed power stations in the region, photovoltaic clusters can maximize land use efficiency, reduce grid connection costs and improve energy supply capacity. However, the geographical distribution of photovoltaic power stations is remarkably extensive and dispersed, covering complex scenarios such as deserts, mountains, and agricultural-photovoltaic complementarity. The number of equipment is huge (a single cluster can reach thousands to tens of thousands of photovoltaic modules, inverters and sensors), and is faced with the dynamic influence of multiple environmental variables such as day and night temperature differences, sandstorms, rain and snow, and electromagnetic environment. The traditional decentralized management model relies on manual inspections and single-point monitoring, which has three core pain points: First, real-time monitoring is difficult, relying on manual data collection at regular intervals, unable to capture instantaneous changes such as light fluctuations and voltage anomalies on a second-scale; second, power regulation lags and lacks global coordinated control capabilities. When the grid load suddenly changes or local equipment fails, it can easily lead to an imbalance between the cluster's overall power output and grid demand; third, fault response is slow, equipment abnormality alarms are delayed, and it is difficult to accurately locate the interference source or fault point, often leading to the risk of cascading outages. These problems directly lead to safety hazards such as voltage over-limit and frequency fluctuations when photovoltaic energy is connected to the grid, as well as economic losses such as increased power curtailment and low power consumption efficiency. There is an urgent need for the support of intelligent and intensive management systems.

[0003] However, electromagnetic interference generated by surrounding industrial equipment (such as inverters, motors, and high-frequency heating devices) and high-voltage transmission lines is becoming a major challenge to the efficient operation of photovoltaic clusters. The switching devices of industrial equipment generate broadband electromagnetic noise when operating at high frequencies. This electromagnetic interference enters the sensor circuits and communication links of the photovoltaic system through spatial radiation or conduction coupling, resulting in reduced sensor signal acquisition accuracy and impaired communication stability in the photovoltaic cluster operation control system, thereby affecting the accuracy and real-time performance of data transmission. Summary of the Invention

[0004] Technical problems solved

[0005] In response to the shortcomings of the existing technology, the present invention provides a photovoltaic cluster operation control system and method, which solves the problem that electromagnetic interference causes the sensor signal acquisition accuracy of the photovoltaic cluster operation control system to decrease and the communication stability to be damaged, thereby affecting the accuracy and real-time performance of data transmission.

[0006] Technical Solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a photovoltaic cluster operation control system and method, including the following specific steps and modules: Step 1: Start real-time collection of voltage data, light intensity data and signal data, and perform comprehensive analysis to obtain interference factors; Step 2: Determine whether the operation of the photovoltaic cluster is interfered with based on the interference factors; Step 3: If interference is determined, control is performed through the anti-interference module; if it is determined to be normal, the detection is terminated.

[0008] Furthermore, the specific method of obtaining the interference factor is as follows: performing comprehensive calculation on the voltage data to obtain the voltage anomaly parameter, performing comprehensive calculation on the light intensity data to obtain the light intensity anomaly parameter, performing comprehensive calculation on the signal data to obtain the signal anomaly parameter, and performing standardization processing on the voltage anomaly parameter, the light intensity anomaly parameter and the signal anomaly parameter to remove the dimension and perform comprehensive calculation to obtain the interference factor.

[0009] Furthermore, the specific method of the interference factor is: Where GY represents the interference factor, DC represents the voltage abnormality parameter, GC represents the light intensity abnormality parameter, XC represents the signal abnormality parameter, and j is a positive real number.

[0010] Furthermore, the voltage anomaly parameter is specifically obtained as follows: according to the time series, the voltage data of the next second and the voltage data of the previous second are sequentially calculated to obtain a voltage deviation value, the absolute value of the voltage deviation value is taken, and the voltage deviation value is summed to obtain the voltage anomaly parameter.

[0011] Furthermore, the specific method of the voltage abnormality parameter is: Among them, DC represents the voltage abnormality parameter, DY i+1 Indicates the voltage data of the next second, DY i It represents the voltage data of the last second, and t represents time.

[0012] Furthermore, the specific method for obtaining the light intensity abnormality parameter is as follows: performing fluctuation calculation on the light intensity data to obtain the light intensity fluctuation value, and according to the time series, performing difference calculation on the light intensity fluctuation value of the next second and the light intensity fluctuation value of the previous second in turn to obtain the light intensity fluctuation deviation value, taking the absolute value of the light intensity fluctuation deviation value, and summing the light intensity fluctuation deviation values to obtain the light intensity abnormality parameter.

[0013] Furthermore, the specific method of the abnormal light intensity parameter is: Among them, DC represents the abnormal light intensity parameter, GB i+1Indicates the light intensity fluctuation value for the next second, GB i It represents the light intensity fluctuation value of the last second, and t represents time.

[0014] Furthermore, the specific method of obtaining the light intensity fluctuation value is as follows: the light intensity data is averaged to obtain the light intensity mean, which is used to measure the standard for the fluctuation of the light intensity data; the light intensity data is subtracted from the light intensity mean and then squared to obtain the sub-light intensity fluctuation value; the sub-light intensity fluctuation values are summed to obtain the light intensity fluctuation value.

[0015] Furthermore, the signal abnormality parameter is specifically obtained in the following manner: standard signal data is set, and the signal abnormality parameter is obtained by performing a difference calculation between the standard signal data and the signal data.

[0016] Furthermore, the system includes: a data acquisition module, a data analysis module and an anti-interference module; the data acquisition module is used to collect voltage data, light intensity data and signal data in real time and send them to the data analysis module; the data analysis module is used to receive and analyze the data sent by the data acquisition module to obtain an interference factor, and judge whether the photovoltaic cluster is interfered with based on the interference factor. If it is interfered with, an instruction is sent to the anti-interference module; the anti-interference module is used to receive the instruction sent by the data analysis module and shield the interference source.

[0017] Beneficial effects

[0018] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0019] 1. By collecting three core parameters, voltage, light intensity, and signal data, in real time, a multi-dimensional interference assessment system is constructed. The voltage anomaly parameters and light intensity fluctuation deviation are calculated using time series differences. The difference between the actual signal value and the standard value is combined and fused into a comprehensive interference factor after standardization. This method breaks through the limitations of single parameter detection and systematically quantifies the impact of multiple sources of interference, such as electromagnetic interference and environmental fluctuations, providing a comprehensive and scientific basis for interference judgment and solving the problems of one-sided and extensive traditional detection.

[0020] 2. Interference factors are compared in real time using preset thresholds to accurately identify interference states. The anti-interference module actively shields interference sources based on instructions, specifically addressing problems such as sensor signal distortion and communication interruptions. This mechanism enables real-time monitoring and dynamic response to interference, avoiding risks such as equipment malfunction and power regulation lags. It significantly improves the operational stability of photovoltaic clusters in complex environments and provides automated and intelligent support for the efficient management of large-scale photovoltaic systems.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a photovoltaic cluster operation control method according to the present invention.

[0023] Figure 2 This is the structural diagram of the photovoltaic cluster operation control system of the present invention. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0025] It should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprise," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0026] like Figure 1 As shown, an embodiment of the present invention provides a photovoltaic cluster operation control method, which includes the following specific steps:

[0027] Step 1: Start collecting voltage data in real time through the voltage sensor, light intensity data in real time through the illumination sensor, and signal data in real time through the RF power sensor. Analyze whether the photovoltaic cluster is interfered with by using the voltage data, light intensity data, and signal data. Filter and reduce noise on the voltage data, light intensity data, and signal data to help improve the data quality of the voltage data, light intensity data, and signal data. Perform comprehensive calculation on the voltage data to obtain voltage anomaly parameters. Perform comprehensive calculation on the light intensity data to obtain light intensity anomaly parameters. Perform comprehensive calculation on the signal data to obtain signal anomaly parameters. Standardize the voltage anomaly parameters, light intensity anomaly parameters, and signal anomaly parameters to remove dimensions and perform comprehensive calculations to obtain interference factors.

[0028]

[0029] Among them, GY represents the interference factor, which reflects whether the PV cluster is disturbed; DC represents the voltage anomaly parameter, which reflects whether the voltage is abnormal; GC represents the light intensity anomaly parameter, which reflects whether the light intensity is abnormal; XC represents the signal anomaly parameter, which reflects whether the signal is abnormal; j is a positive real number such that ln(j+DC) holds; k is a positive real number such that ln(k+GC) holds; l is a positive real number such that ln(l+XC) holds.

[0030] The specific method for obtaining voltage anomaly parameters is as follows:

[0031] According to the time series, the voltage data of the next second is calculated in turn with the voltage data of the previous second to obtain the voltage deviation value. The absolute value of the voltage deviation value is taken to facilitate subsequent calculations. The voltage deviation values are summed to obtain the voltage anomaly parameter;

[0032] The specific method of voltage abnormal parameters is:

[0033]

[0034] Among them, DC represents the voltage abnormality parameter, DY i+1 Indicates the voltage data of the next second, DY i It represents the voltage data of the last second, and t represents time.

[0035] The specific method for obtaining the abnormal light intensity parameters is as follows:

[0036] Perform fluctuation calculation on the light intensity data to obtain the light intensity fluctuation value. According to the time series, perform difference calculation on the light intensity fluctuation value of the next second and the light intensity fluctuation value of the previous second to obtain the light intensity fluctuation deviation value. Take the absolute value of the light intensity fluctuation deviation value to facilitate subsequent calculations. Sum the light intensity fluctuation deviation values to obtain the light intensity abnormality parameter.

[0037] The specific method for light intensity anomaly parameters is:

[0038]

[0039] Among them, DC represents the abnormal light intensity parameter, GB i+1 Indicates the light intensity fluctuation value for the next second, GB i It represents the light intensity fluctuation value of the last second, and t represents time.

[0040] The specific method of obtaining the light intensity fluctuation value is as follows:

[0041] The light intensity data is averaged to obtain the light intensity mean, which is used to measure the standard for light intensity data fluctuation. The light intensity data is subtracted from the light intensity mean and then squared to obtain the sub-light intensity fluctuation value. The sub-light intensity fluctuation values are summed to obtain the light intensity fluctuation value.

[0042] The specific method for obtaining signal abnormality parameters is as follows:

[0043] Standard signal data is set to reflect the signal of the photovoltaic cluster under normal conditions. The signal abnormality parameters are obtained by performing difference calculation between the standard signal data and the signal data.

[0044] The specific method of signal abnormal parameters is:

[0045] XC = |BZ-XZ|;

[0046] Among them, CX represents the signal abnormality parameter, BZ represents the standard signal data, and XZ represents the signal data.

[0047] Step 2: Set the interference threshold and perform real-time comparison between the interference factor and the interference threshold. If the interference factor is greater than the interference threshold, interference is determined; if the interference factor is less than or equal to the interference threshold, it is determined to be normal.

[0048] Step 3: If interference is detected, the anti-interference module is used to control the system. The anti-interference module prevents interference to the photovoltaic cluster. If the system is normal, the detection ends.

[0049] like Figure 2 As shown, an embodiment of the present invention provides a photovoltaic cluster operation control system, which includes the following specific modules:

[0050] Data acquisition module: used to collect voltage data, light intensity data and signal data in real time and send them to the data analysis module;

[0051] Data analysis module: used to receive and analyze the data sent by the data acquisition module to obtain the interference factor, and judge whether the photovoltaic cluster is interfered with based on the interference factor. If it is interfered with, it sends instructions to the anti-interference module;

[0052] Anti-interference module: used to receive instructions sent by the data analysis module and shield interference sources.

[0053] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A photovoltaic cluster operation control method, characterized by: The specific steps include: Step 1: Start collecting voltage data, light intensity data, and signal data in real time, and perform comprehensive analysis to obtain interference factors; Step 2: Determine whether the operation of the photovoltaic cluster is disturbed based on the interference factor; Step 3: If interference is detected, the anti-interference module is used for control. If normal, the detection is terminated.

2. A photovoltaic cluster operation control method according to claim 1, characterized in that: The specific method of obtaining the interference factor is as follows: The voltage data is comprehensively calculated to obtain the voltage anomaly parameters, the light intensity data is comprehensively calculated to obtain the light intensity anomaly parameters, and the signal data is comprehensively calculated to obtain the signal anomaly parameters. The voltage anomaly parameters, light intensity anomaly parameters and signal anomaly parameters are standardized to remove the dimensions and comprehensively calculated to obtain the interference factor.

3. A photovoltaic cluster operation control method according to claim 2, characterized in that: The specific method of the interference factor is: Where GY represents the interference factor, DC represents the voltage abnormality parameter, GC represents the light intensity abnormality parameter, XC represents the signal abnormality parameter, and j is a positive real number.

4. A photovoltaic cluster operation control method according to claim 2, characterized in that: The specific method for obtaining the voltage abnormality parameter is as follows: According to the time series, the voltage data of the next second and the voltage data of the previous second are calculated in turn to obtain the voltage deviation value, the absolute value of the voltage deviation value is taken, and the voltage deviation values are summed to obtain the voltage anomaly parameter.

5. A photovoltaic cluster operation control method according to claim 4, characterized in that: The specific method of the voltage abnormality parameter is: Among them, DC represents the voltage abnormality parameter, DY i+1 Indicates the voltage data of the next second, DY i It represents the voltage data of the last second, and t represents time.

6. A photovoltaic cluster operation control method according to claim 2, characterized in that: The specific method for obtaining the abnormal light intensity parameter is as follows: The light intensity data is subjected to fluctuation calculation to obtain the light intensity fluctuation value. According to the time series, the light intensity fluctuation value of the next second is calculated in turn with the light intensity fluctuation value of the previous second to obtain the light intensity fluctuation deviation value. The absolute value of the light intensity fluctuation deviation value is taken, and the light intensity fluctuation deviation values are summed to obtain the light intensity anomaly parameter.

7. The photovoltaic cluster operation control method according to claim 6, characterized in that: The specific method of the abnormal light intensity parameter is as follows: Among them, DC represents the abnormal light intensity parameter, GB i+1 Indicates the light intensity fluctuation value for the next second, GB i It represents the light intensity fluctuation value of the last second, and t represents time.

8. The photovoltaic cluster operation control method according to claim 6, characterized in that: The specific method for obtaining the light intensity fluctuation value is as follows: The light intensity data is averaged to obtain the light intensity mean, which is used to measure the standard for light intensity data fluctuation. The light intensity data is subtracted from the light intensity mean and then squared to obtain the sub-light intensity fluctuation value. The sub-light intensity fluctuation values are summed to obtain the light intensity fluctuation value.

9. The photovoltaic cluster operation control method according to claim 2, characterized in that: The specific method for obtaining the signal abnormality parameters is as follows: Set standard signal data, perform difference calculation between the standard signal data and the signal data, and obtain signal anomaly parameters.

10. A photovoltaic cluster operation control system, used to implement a photovoltaic cluster operation control method according to any one of claims 1 to 9, characterized in that: The system includes: a data acquisition module, a data analysis module and an anti-interference module; Data acquisition module: used to collect voltage data, light intensity data and signal data in real time and send them to the data analysis module; Data analysis module: used to receive and analyze the data sent by the data acquisition module to obtain the interference factor, and judge whether the photovoltaic cluster is interfered with based on the interference factor. If it is interfered with, it sends instructions to the anti-interference module; Anti-interference module: used to receive instructions sent by the data analysis module and shield interference sources.

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